Parameter Uncertainties Influencing Vehicle Lateral Dynamics Steady State Applications

In this paper, the influence of uncertain model parameters on vehicle lateral dynamics steady states is studied. These steady states are widely used in driver assistant systems and enable highly automated driving functions. A methology for propagating random variables through the single-track vehicle model is presented. The random variables are described using continuous probability density functions. It is shown, that the influence of parameter uncertanties scales differently to different steady states. The effect on the path curvature and the lateral acceleration is highlighted. An example for a fault detection scheme is given and analysed in context of the given uncertainty. The faults that can be detected without violating a given true-positive rate and a given false-positive rate are calculated. The method can be used to quickly identify possible problems arising from uncertain parameters.